Probabilistic Power Distribution Considering Uncertainty in Load and Distributed Generators Using Cumulant and Truncated Versatile Distribution

Abstract

Enhanced power flow has a significant effect on the desirable performance of the power system. Implementing of the fair power flow prevents the power system from overload or damage of the elements and provides stable parameters. Considering different distributed generators (DGs) and various loads, balance in the power distribution is a key factor of the stability and reliability of the power system. On the other hand, the uncertainty of DGs and loads causes underestimation of power in the system, which results in a main challenge. In this paper to overcome this challenge, a probabilistic power distribution approach based on using Cumulant and truncated versatile distribution techniques is proposed. Using this approach, the probabilistic models of DGs and load are suggested where the power distribution is desirably performed using adaptive droop control process and employing Cumulant distribution and truncated versatile distribution. Thus, the degradation effect of the uncertainties is compensated where the frequency/voltage deviation from the reference values is minimized. Adaptive droop approach is employed to achieve the stable frequency/voltage, which leads to improved power flow in the total parts of the power system and avoidance in power redistribution cost Simulation results show the efficiency of the proposed method to improve the performance of the system and cost reduction.